Senior AI Data Engineer: GenAI & Enterprise AI on Azure

EPAM; Greater London; In loco; GBP 110.000 - 170.000; Tempo pieno

Vantaggi offerti da questo lavoro

EPAM ESPP

Life insurance & income protection

Private medical & dental

Employee Assistance Program

Competitive pension

Commuter benefits & tech schemes

Learning & development & courses

Bonus & LTI programs

Descrizione del lavoro

EPAM is seeking a senior AI/data engineering leader to design, build and productionize enterprise-grade AI and GenAI solutions on Azure and Databricks. You will drive scalable AI apps, intelligent agents, and data-driven workflows powered by LLMs and modern AI frameworks.

You will lead hands‑on development of end-to-end data pipelines, RAG apps, and agent orchestration, while partnering with stakeholders to translate requirements into scalable, reliable solutions.

Competenze

• Bachelor’s or Master’s degree in Statistics, Mathematics, Econometrics, Computer Science or a related field
• 8+ years of experience delivering data engineering, machine learning or AI solutions in enterprise environments
• Strong AI Data Engineering expertise with experience building production‑grade AI and GenAI systems
• Hands‑on experience with Azure AI Foundry, Azure cloud services and Databricks AI technologies
• Deep understanding of Large Language Models (LLMs) and Retrieval‑Augmented Generation (RAG) solutions
• Strong experience with MLflow, GenAI evaluation frameworks and model benchmarking methodologies
• Advanced programming skills in Python and SQL with strong knowledge of data modeling and ETL/ELT processes
• Solid understanding of Delta Lake, Delta Live Tables, Unity Catalog, Spark Structured Streaming and large‑scale data processing
• Experience with Azure Data Factory (ADF), Qlik Replicate and modern data architecture practices
• Excellent communication, stakeholder management, problem‑solving skills and commitment to high‑quality delivery
• Bonus: Experience with LangGraph, AutoGen or agent orchestration frameworks; governance, security and mentoring engineers

Mansioni

• Develop and evaluate AI, GenAI and Agentic AI solutions using enterprise AI platforms and frameworks
• Build and optimize Retrieval‑Augmented Generation (RAG) applications, including embedding strategies, prompt engineering and evaluation processes
• Design, develop and deploy AI agents using frameworks such as LangChain, LangGraph, AutoGen and similar technologies
• Create scalable AI workflows using Databricks, MLflow, Azure AI Foundry and cloud‑native services
• Build and maintain robust data pipelines using modern data engineering practices and streaming technologies
• Deploy AI applications and services using Azure OpenAI, Azure AI Foundry, Databricks AI tools and Docker
• Design and execute evaluation frameworks to measure model quality, accuracy, reliability and reproducibility
• Implement CI/CD pipelines, testing frameworks, code quality controls and GitHub‑based development processes
• Collaborate with stakeholders to translate business requirements into scalable AI solutions
• Contribute to architecture decisions, technical roadmaps and backlog definition while supporting delivery from prototype to production

Conoscenze

8+ years experience in data eng/ML/AI

AI Data Engineering

Python & SQL

LLMs & RAG

Azure AI Foundry & Databricks

MLflow & GenAI eval

ETL/ELT & data modeling

Delta Lake / Delta Live Tables / Unity

ADF & Qlik Replicate

Communication & stakeholder mgmt

Formazione

Bachelor’s or Master’s degree in Statistics/Math/CS

Strumenti

Azure Databricks

Azure AI Foundry

Databricks AI tools

MLflow

Qlik Replicate

Docker

LangChain / LangGraph / AutoGen

Descrizione del lavoro

EPAM is seeking a senior AI/data engineering leader to design, build and productionize enterprise-grade AI and GenAI solutions on Azure and Databricks. You will drive scalable AI apps, intelligent agents, and data-driven workflows powered by LLMs and modern AI frameworks.

You will lead hands‑on development of end-to-end data pipelines, RAG apps, and agent orchestration, while partnering with stakeholders to translate requirements into scalable, reliable solutions.